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An Efficient Profiling Attack to Real Codes of PIC16F690 and ARM Cortex-M3
2020
IEEE Access
This paper presents a new and efficient method based on power analysis, hierarchical recognition of instructions, and machine learning for reverse engineering of the instructions of PIC16F690 as an 8-bit microcontroller and LPC1768, which includes an ARM Cortex-M3 core as a 32-bit platform. Both dynamic and static power consumption were considered and analyzed. The instructions were classified in different Hamming weight groups using ensemble classification algorithms along with the
doi:10.1109/access.2020.3043395
fatcat:rcgkj523efhmverofltupemocm